Every piece of content has explicit visibility rules.
Psychiatric findings, nursing reports, and assessments each have separate is_visible_to_nursing and is_visible_to_relatives flags — controllable per entry and per facility policy.
Trust
Good health-tech platforms don't just reassure. They prove.
Trust shows how Digital Neurocare handles patient data, role permissions, interfaces, and public forms responsibly — as built-in operational quality, not a retrospective privacy statement.
- Role-based visibility control — from nursing notes to psychiatric findings
- Complete audit logs for every access and every change
- FHIR R4 interfaces for revision-safe data integration
Trust layer
Trust is product, process, and operations at the same time.
The trust page explains not just policies but the real behavior of the platform: how roles are controlled, how entries are secured, and how AI suggestions remain separate from clinical findings.
Every access and every change is logged in a revision-safe audit trail.
Audit logs include actor, resource, action, timestamp, and justification for break-glass access — for internal quality reviews and external auditors.
The original text of every entry is preserved immutably.
ClinicalDocumentationEntry.raw_text is never deleted or overwritten. Structured extraction adds to it — it never replaces it.
FHIR R4 interfaces are communicated openly.
System boundaries, API connections, and integration architecture are presented as part of the trust foundation — not hidden implementation detail.
Controls
How data, roles, and integrations work together here.
The trust page explains actual website behavior, not only policy copy.
Role-based visibility control
No content is automatically visible to everyone. Every role sees only what is explicitly released.
- Nursing, physician, therapist, coordinator, management, admin
Six roles with differentiated access rights — psychiatric findings remain role-protected, nursing documentation stays team-accessible.
- Break-glass access with mandatory justification
Emergency access to protected content requires a justification and is fully logged.
AI governance and raw-text protection
AI content is always labeled — and can never become clinical truth without human oversight.
- AI suggestions always require human confirmation
Medication decisions generated with AI support only become active after an authorized clinician explicitly confirms them.
- Raw text as an indestructible safety layer
Every clinical entry holds the complete original text — independent of subsequent structuring or AI analysis.
FAQ
Trust without fog.
Important answers about privacy, operations, and forms.
Where do website contact requests go?
Requests are stored persistently and can be forwarded by SMTP to a dedicated team inbox. No clinically exposed public channel.
Why no open health-data forms on the site?
Because the marketing site is not a clinical intake channel. Sensitive information belongs in protected clinical workflows — not a public web form.
How are AI suggestions separated from clinical findings?
All AI-generated content is labeled with source='ai_assisted' and never appears without labeling in the clinical record. Medication suggestions always require explicit confirmation by an authorized clinician.